Author: Claire Dunbar
Dunbar, Claire, 2023 Establishing the sleep disruption characteristics of wind turbine compared to traffic noise using quantitative electroencephalography with spectral power analysis, Flinders University, College of Education, Psychology and Social Work
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Sleep is important for health and normal physiological and psychological wellbeing and
daytime function. A well-known source of sleep disruption is nocturnal exposure to noise such as
from air, road, and rail traffic. The consequences of consistently disrupted sleep can result in serious
health deficits including hypertension, cardiovascular disease, impaired mental health, and daytime
functioning. Therefore, all reports of significant sleep disruption warrant examination using
appropriate sleep and noise assessment methods. Another source of nocturnal noise, increasing in
its presence as the world attempts to reduce carbon emissions, is from wind farms. Noise from wind
farms has more dominant low frequency components compared to other noise sources and its
effects on sleep are currently unclear and need further investigation. Subjective reports of impaired
sleep in some individuals living in the vicinity of wind farms have prompted the need for
comprehensive investigation of the possible impact of wind farm noise (WFN) on sleep using
objective measures of sleep in well controlled experimental studies. The gold-standard objective
measure of sleep is polysomnography (PSG). However, the standard macrostructure sleep measures
such as total sleep time and time spent in different sleep stages may not be sufficiently sensitive to
capture more subtle changes within the EEG that could potentially differentially impact effective
sleep quality and measures of daytime functioning.
This thesis used quantitative electroencephalography (qEEG) to objectively assess and
compare the impact of traffic noise and wind farm noise on sleep. qEEG is likely to be more
sensitive than traditional sleep assessment methods for evaluating noise effects on the sleep EEG.
For example, traditional PSG analysis may find no effects of WFN on total sleep time, or the
amount of time spent in individual sleep stages. However, it must be recognised that the definition
of deeper sleep stages as distinguished from lighter stages of sleep is based on manual scoring of 30
second epochs and somewhat arbitrary and crude criteria dividing sleep stages. Potentially
important differences within any given sleep stage in terms of amplitude, frequency, and power
could easily be missed. These differences may importantly contribute to the functional effects of
deep sleep on the overall recuperative properties of the whole sleep period. If qEEG is sensitive to
noise exposure but macrostructural analysis is not, qEEG analysis may be recommended for more
comprehensive assessments of sleep beyond traditional macrostructure sleep analysis. Furthermore,
such results would provide valuable feedback for informing noise guidelines and mitigation
strategies which are currently based on more typically mid to high frequency dominated noise
sources such as road traffic noise.
Keywords: road traffic noise, wind turbine noise, sleep, sleep disruption, spectral power, quantitative electroencephalography, polysomnography
Subject: Psychology thesis
Thesis type: Doctor of Philosophy
Completed: 2023
School: College of Education, Psychology and Social Work
Supervisor: Leon Lack